What a used PlayStation 4 actually sells for on eBay

"How much is a PlayStation 4 worth?" has one honest answer: whatever comparable units are actually selling for right now. Retail prices, trade-in quotes, and asking prices all mislead. The only number that matters is the completed sale price, what a buyer actually paid.

So we pulled a page of recent completed PlayStation 4 console sales from eBay (US marketplace) and measured the distribution. Here is what the resale market looked like on the sample date.

The numbers

From 142 completed console sales (used units, excluding obvious parts/broken listings):

• Median sale price: $99.50 (the honest "what it's worth" number)
• Typical range (middle 50%): $80 to $127.50
• Full observed range: $30 (untested/parts-adjacent) to $350 (bundles, higher-capacity or boxed units)
• Average: $110.21 (pulled up by bundles, which is why the median is the better single number)

The takeaway: a standard used PS4 in working condition clusters around $80 to $130, with a median near $100. Bundles with extra controllers and games are what push the top of the range.

Why the median, not the average

A handful of large bundles drag the average up. The median (middle value) is far more robust for "what's it worth" questions because a few outliers cannot distort it. When you price an item to sell, the median of recent comparable sales is the number to anchor on.

How to reproduce this (and keep it current)

This snapshot ages the moment it is published, resale values move weekly. Instead of trusting a static number, pull live completed sales yourself. One request returns the raw sales; you compute the median in a couple of lines:

curl 'https://api.ebaysoldlistingsapi.com/scrape?keyword=playstation+4+console' \
  -H 'Authorization: Bearer YOUR_API_KEY'

# Python: median of completed sale prices
import requests, statistics
r = requests.get(
    "https://api.ebaysoldlistingsapi.com/scrape",
    params={"keyword": "playstation 4 console"},
    headers={"Authorization": "Bearer YOUR_API_KEY"},
).json()
prices = [float(i["soldPrice"]) for i in r["results"] if i.get("soldPrice")]
print("median:", statistics.median(sorted(prices)))

Each response is raw completed sales with price, date, condition, shipping, and seller, so you can filter by condition, drop outliers, or chart the trend however your use case needs.